Key acquisition method and related equipment

Abstract

The invention discloses a secret key obtaining method and related equipment, and relates to the technical field of information security, and the method comprises the steps: obtaining a current secret key request, obtaining first feature data corresponding to a current environment in response to the current secret key request, loading multiple segments of target password data corresponding to a secret key from a memory, and storing the multiple segments of target password data corresponding to the secret key; determining first feature data in the multiple segments of target password data, determining second feature data in the multiple segments of target password data, and based on the first feature data, the second feature data and a preset data feature loss model, obtaining a data feature loss result of the first feature data and the second feature data, and if the data feature loss result is smaller than or equal to a preset loss threshold, obtaining target key data from the multiple segments of target password data. According to the method and the device, the dynamic password data with the feature data is generated through the environment features, and the key reading permission is confirmed by verifying the environment features, so that the key security is effectively improved.

Description

Technical Field

[0001] The present application relates to the field of information security technology, and in particular to a key acquisition method and related equipment. Background Art

[0002] With the rapid development of science and technology, in order to ensure information security, information needs to be encrypted and identity authenticated. As a result, key security management is becoming increasingly important.

[0003] In the related art, the key acquisition device generates and stores the key. When receiving the key acquisition instruction, it only needs to perform a simple verification to obtain the key. In the actual key acquisition process, the key acquisition device generates a static key and directly reads it after receiving the user's request, which is less secure.

[0004] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] The main purpose of this application is to provide a key acquisition method and related equipment, aiming to solve the technical problem that the key acquisition device generates a static key and directly reads it after obtaining a user request, which has low security.

[0006] To achieve the above purpose, the present application proposes a key acquisition method, the method comprising: Obtaining a current key request, and in response to the current key request, obtaining first characteristic data corresponding to the current environment; Loading multiple segments of target cryptographic data corresponding to the key from the memory, and determining second characteristic data in the multiple segments of target cryptographic data, wherein the target cryptographic data includes the second characteristic data and target key data; Based on the first feature data, the second feature data and a preset data feature loss model, obtaining data feature loss results of the first feature data and the second feature data, wherein the preset data feature loss model is a trained data feature loss model; If the data feature loss result is less than or equal to a preset loss threshold, target key data is obtained from the multiple segments of target password data.

[0007] In one embodiment, before the step of loading the multiple segments of target cryptographic data corresponding to the key from the memory, the method further includes: receiving a password generation instruction, and acquiring second characteristic data corresponding to the environmental information in response to the password generation instruction; Based on the second characteristic data, using a preset password generation algorithm to generate initial password data, wherein the initial password data includes target key data and the second characteristic data; The initial password data is segmented to obtain multiple segments of target password data, and the target password data is randomly stored in different memories.

[0008] In one embodiment, the step of loading multiple segments of target cryptographic data corresponding to the key from the memory and determining the second characteristic data in the multiple segments of target cryptographic data further includes: Loading multiple sets of target cryptographic data corresponding to the key from the memory; Based on a preset data matching relationship algorithm, the correlation between two sets of target password data is obtained; The two groups of target password data with the greatest correlation are spliced ​​to obtain initial password data, and characteristic information in the initial password data is determined.

[0009] In one embodiment, if the data feature loss result is less than or equal to a preset loss threshold, the step of obtaining target key data from the multiple segments of target password data further includes: If the data characteristic loss result is less than or equal to a preset loss threshold, obtaining target key data from the target password data; If the data feature loss result is greater than a preset loss threshold, the current access permission is obtained; if the current access permission is to allow access, the key data is obtained from the target password data.

[0010] In one embodiment, after the step of obtaining the target key data from the multiple segments of target password data, the step further includes: Obtaining a historical key request instruction, and determining a usage frequency of a key based on the current key request instruction and the historical key request instruction; Determining a key update time based on the usage frequency and a preset number of key usage times; Based on the key update time, new target cryptographic data is generated, and the target cryptographic data is replaced with the new target cryptographic data.

[0011] In one embodiment, before the step of based on the environment information data, the feature information data and the preset data feature loss model, it also includes: Obtaining a current data feature loss model, first sample data, and second sample data, wherein the data feature loss results of the first sample data and the second sample data are the first data feature loss results; Based on the current data feature loss model, the first sample data, and the second sample data, obtaining second data feature loss results of the first sample data and the second sample data; Calculating the first data feature loss result and the second data feature loss result to obtain a loss difference; If the loss difference is greater than a preset loss difference, adjusting the parameters of the current data feature loss model and recording the number of adjustments; Based on the adjusted current data feature loss model, return to the step of obtaining the second data feature loss result of the first sample data and the second sample data based on the current data feature loss model, the first sample data and the second sample data, until the loss difference is less than or equal to the preset loss difference, or the number of adjustments is equal to the preset number of adjustments, and set the current data feature loss model corresponding to the minimum loss difference as the preset data feature loss model.

[0012] In addition, to achieve the above purpose, the present application also proposes a key acquisition device, the key acquisition device comprising: An acquisition instruction module, the acquisition instruction module is used to acquire a current key request, and in response to the current key request, acquire first characteristic data corresponding to the current environment; A determination module, the determination module is used to load multiple segments of target cryptographic data corresponding to the key from a memory, and determine second characteristic data in the multiple segments of target cryptographic data, wherein the target cryptographic data includes the second characteristic data and target key data; A calculation module, wherein the calculation module is used to obtain data feature loss results of the first feature data and the second feature data based on the first feature data, the second feature data and a preset data feature loss model, wherein the preset data feature loss model is a trained data feature loss model; A key acquisition module is used to acquire target key data from the multiple segments of target password data if the data feature loss result is less than or equal to a preset loss threshold.

[0013] In one embodiment, the determining module includes: A receiving unit, configured to receive a password generation instruction, and acquire second characteristic data corresponding to the environmental information in response to the password generation instruction; A generating unit, configured to generate initial password data based on the second characteristic data using a preset password generation algorithm, wherein the initial password data includes target key data and the second characteristic data; The segmentation unit is used to segment the initial password data to obtain multiple segments of target password data, and randomly store the target password data in different memories.

[0014] In one embodiment, the determining module further includes: The loading unit loads multiple groups of target cryptographic data corresponding to the key from the memory; A first acquisition unit, used to obtain the correlation between two sets of target password data based on a preset data matching relationship algorithm; The splicing unit is used to splice the two groups of target password data with the greatest correlation to obtain initial password data and determine the characteristic information in the initial password data.

[0015] In one embodiment, the key acquisition module includes: A second acquisition unit, configured to acquire target key data from the target cryptographic data if the data feature loss result is less than or equal to a preset loss threshold; The third acquisition unit is used to obtain the current access permission if the data feature loss result is greater than a preset loss threshold, and to obtain the key data from the target password data if the current access permission is to allow access.

[0016] In one embodiment, the key acquisition module further includes: A first determining unit, configured to obtain a historical key request instruction, and determine a usage frequency of a key based on the current key request instruction and the historical key request instruction; A second determining unit, configured to determine a key update time based on the usage frequency and a preset key usage count; The replacement unit is used to generate new target cryptographic data based on the key update time, and replace the target cryptographic data with the new target cryptographic data.

[0017] In one embodiment, the calculation module includes: a fourth acquisition unit, configured to acquire a current data feature loss model, first sample data, and second sample data, wherein data feature loss results of the first sample data and the second sample data are first data feature loss results; a fifth acquisition unit, configured to obtain a second data feature loss result of the first sample data and the second sample data based on the current data feature loss model, the first sample data, and the second sample data; A calculation unit, configured to calculate the first data feature loss result and the second data feature loss result to obtain a loss difference; A judgment unit, configured to adjust the parameters of the current data feature loss model if the loss difference is greater than a preset loss difference, and record the number of adjustments; A training unit is used to return the step of obtaining the second data feature loss result of the first sample data and the second sample data based on the current data feature loss model, the first sample data and the second sample data, based on the adjusted current data feature loss model, until the loss difference is less than or equal to the preset loss difference, or the number of adjustments is equal to the preset number of adjustments, and set the current data feature loss model corresponding to the minimum loss difference as the preset data feature loss model.

[0018] In addition, to achieve the above-mentioned purpose, the present application also proposes a key acquisition device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the key acquisition method described above.

[0019] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the key acquisition method described above are implemented.

[0020] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the key acquisition method described above are implemented.

[0021] One or more technical solutions proposed in this application have at least the following technical effects: The present application proposes a key acquisition method and related equipment. In the related technology, the key acquisition equipment generates a static key and directly reads it after obtaining a user request, which has low security. In the present application, first, a current key request is obtained, and in response to the current key request, first feature data corresponding to the current environment is obtained. Then, multiple segments of target password data corresponding to the key are loaded from the memory, and second feature data in the multiple segments of target password data are determined, wherein the target password data includes second feature data and target key data. Furthermore, based on the first feature data, the second feature data and a preset data feature loss model, a data feature loss result of the first feature data and the second feature data is obtained, wherein the preset data feature loss model is a trained data feature loss model. Finally, if the data feature loss result is less than or equal to a preset loss threshold, target key data is obtained from the multiple segments of target password data.

[0022] It can be understood that the key acquisition device obtains the environmental characteristics when the key request is made, and performs dynamic verification based on the environmental characteristics, thereby effectively improving the security of the key. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0024] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0025] Figure 1 A schematic diagram of a process flow provided for the first embodiment of the method for obtaining a key of the present application; Figure 2 A schematic diagram of the process flow provided for the second embodiment of the key acquisition method of this application; Figure 3 A flowchart of the third embodiment of the method for obtaining a key in this application is provided; Figure 4 This is a schematic diagram of the module structure of the key acquisition device according to an embodiment of the present application; Figure 5 This is a schematic diagram of the device structure of the hardware operating environment involved in the key acquisition method in the embodiment of the present application.

[0026] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0027] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0028] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0029] The main solutions of the embodiments of this application are: In this embodiment, for ease of description, the key acquisition device is used as the execution subject for explanation below.

[0030] Since the key acquisition device in the prior art generates a static key and directly reads it after receiving a user request, the security is low.

[0031] The present application provides a solution, which enables obtaining a current key request, responding to the current key request, obtaining the first characteristic data corresponding to the current environment, loading multiple segments of target password data corresponding to the key from the memory, and determining the second characteristic data in the multiple segments of target password data, and obtaining the data characteristic loss result of the first characteristic data and the second characteristic data based on the first characteristic data, the second characteristic data and the preset data characteristic loss model, and if the data characteristic loss result is less than or equal to the preset loss threshold, obtaining the target key data from the multiple segments of target password data. The present application generates dynamic password data with characteristic data through environmental characteristics, and confirms the key reading authority by verifying the environmental characteristics, thereby effectively improving the key security.

[0032] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a key acquisition device, etc. The following takes the key acquisition device as an example to illustrate this embodiment and the following embodiments.

[0033] Based on this, the present application embodiment provides a key acquisition method, referring to Figure 1 , Figure 1 This is a flowchart of the first embodiment of the key acquisition method of the present application.

[0034] In this embodiment, the key acquisition method includes steps S10 to S40: Step S10, obtaining a current key request, and in response to the current key request, obtaining first characteristic data corresponding to the current environment; It should be noted that the request to obtain the current key means that the key acquisition device receives a request to obtain the currently required key. This key may be used for encrypted communication, access control, data verification or other security operations that require a key.

[0035] After receiving the key request, the key acquisition device will process and respond to the request. The response may include verifying the legitimacy of the request, checking the identity and authority of the requester, and preparing the corresponding key.

[0036] While or after responding to the key request, the key acquisition device collects characteristic data related to the current environment. The "first characteristic data" here may refer to basic information related to the state, condition or attribute of the environment, such as location, network status, etc.

[0037] It should be noted that the characteristic data related to the current environment also includes user characteristic data, such as user fingerprints, the frequency of user button clicks, etc.

[0038] In this embodiment, the specific application scenario may be: In an environment where a key is required to ensure operational security, the key acquisition device detects that the user clicks the "Get Key" button, that is, the key acquisition device receives a key request, then verifies and responds to the request, and finally collects data related to the current environmental status for further processing or analysis. This process is particularly important in the fields of the Internet of Things (IoT), smart homes, security monitoring, etc., because the devices and systems in these fields need to dynamically adjust their operations and responses according to environmental changes.

[0039] Step S20, loading multiple segments of target cryptographic data corresponding to the key from the memory, and determining second characteristic data in the multiple segments of target cryptographic data, wherein the target cryptographic data includes the second characteristic data and target key data; First, the key acquisition device needs to extract the cryptographic data associated with a specific key from memory. This data may be split into multiple parts, each of which contains a part of the key or encrypted information related to it. This split can be for processing efficiency, security, or to meet specific data management requirements.

[0040] Among these segmented password data, the key acquisition device needs to identify and determine specific "second feature data". The "second feature data" here may refer to other important information besides the key itself, such as the type of encryption algorithm, key usage conditions, usage frequency, usage habits, biometrics, and key validity period, etc. This information is crucial for key management and use.

[0041] It can be understood that the target cryptographic data includes the second characteristic data and the target key data, which means that when processing encrypted data, we should not only pay attention to the key itself, but also pay attention to other characteristic data related to the key. These data together constitute a complete encryption information framework to ensure the security and correct use of the data.

[0042] The entire process involves extracting and processing encrypted data from memory, identifying key feature information, and ensuring the integrity and security of this information. This is very important for maintaining system security and data integrity, especially in environments that require high confidentiality and security.

[0043] Specifically, the step of loading multiple segments of target password data corresponding to the key from the memory and determining the second characteristic data in the multiple segments of target password data further includes steps S21 to S23: Step S21, loading multiple groups of target cryptographic data corresponding to the key from the memory; Step S22, obtaining the correlation between the two sets of target password data based on a preset data matching relationship algorithm; It should be noted that the preset data matching relationship algorithm is a predefined algorithm used to identify and analyze the matching relationship or similarity between two sets of data. This algorithm may be built based on statistics, pattern recognition, machine learning or deep learning technology, and aims to discover potential association rules or patterns from the data.

[0044] It is understandable that by applying a preset data matching algorithm, the key acquisition device can evaluate the correlation between the two sets of password data. This correlation may be manifested as similarity in password patterns, consistency in encryption technology, or commonality in usage conditions. The analysis results of the correlation can help identify potential security risks, optimize password management strategies, or enhance security protection measures.

[0045] Step S23, concatenating the two groups of target password data with the greatest correlation to obtain initial password data, and determining feature information in the initial password data.

[0046] It is understandable that, based on the preset data matching relationship algorithm mentioned above, the key acquisition device has identified the maximum correlation between the two sets of target password data. This means that the two sets of data have the strongest similarity or connection in some aspects (such as mode, structure, encryption algorithm, etc.).

[0047] Next, the key acquisition device concatenates the two sets of data, ie, merges them into a continuous data set. This concatenation may be based on a specific rule or algorithm to ensure that the merged data retains its original meaning and structure.

[0048] The result of the splicing is called "initial password data". This initial password data set contains all the information from the two sets of target password data, providing a complete data foundation for further analysis and processing.

[0049] After obtaining the initial password data, the key acquisition device needs to identify and extract the characteristic information therein. Characteristic information refers to key information that can represent or describe the characteristics of the password data, such as the length of the password, the character set used, the type of encryption algorithm, the length of the key, etc.

[0050] It can be understood that determining these characteristic information is crucial to understanding the structure and characteristics of password data, which can be used for further security analysis, password cracking attempts, formulation of security policies, or evaluation of password strength.

[0051] The entire process involves data matching, splicing, and feature extraction, aiming to extract valuable information from multiple password data sets and provide support for security analysis and decision-making.

[0052] Step S30, obtaining data feature loss results of the first feature data and the second feature data based on the first feature data, the second feature data and a preset data feature loss model, wherein the preset data feature loss model is a trained data feature loss model; It should be noted that the first characteristic data and the second characteristic data respectively represent data characteristics collected from different environments or conditions, which can be sensor readings, statistical data, user behavior data, etc., for further analysis and comparison.

[0053] In addition, the preset data feature loss model is a pre-defined and trained model whose purpose is to measure and quantify the difference between two sets of feature data. This model is called a "data feature loss model" because it focuses on evaluating the loss or change of data features.

[0054] In this embodiment, the data feature loss model used is trained, which means that the model has learned how to identify and quantify the differences between feature data through a large amount of data. Such a model can more accurately evaluate the feature loss between new data sets.

[0055] It is understandable that, based on the preset data feature loss model, the key acquisition device can calculate the difference between the first feature data and the second feature data, and this difference is called the "data feature loss result". This result may be a value or a group of values, indicating the similarity or difference between the two sets of data at the feature level.

[0056] Step S40, if the data feature loss result is less than or equal to a preset loss threshold, obtain target key data from the multiple segments of target password data.

[0057] It should be noted that the preset loss threshold is a pre-set threshold used to determine whether the data feature loss result is within an acceptable range.

[0058] In addition, it should be noted that the target key data is the key used to decrypt data and is key information in cryptography.

[0059] In this embodiment, if the data feature loss result calculated by the preset data feature loss model is less than or equal to the preset loss threshold, then the currently attempted key can be considered correct or valid. In this case, the algorithm extracts the target key data from the multiple segments of target password data, that is, finds the correct key.

[0060] This method is often used for password cracking or verification, especially in some attack scenarios in cryptography, such as differential attacks, side channel attacks, etc., to try to crack the password by comparing expected and actual data features.

[0061] Specifically, if the data feature loss result is less than or equal to a preset loss threshold, the step of obtaining target key data from the multiple segments of target password data further includes steps S41-S42: Step S41, if the data feature loss result is less than or equal to a preset loss threshold, obtaining target key data from the target password data; Step S42: if the data feature loss result is greater than a preset loss threshold, obtain the current access permission; if the current access permission is to allow access, obtain the key data from the target password data.

[0062] It is understandable that when the data feature loss result is greater than the preset loss threshold, the key acquisition device will check the access rights of the current user. Access rights are the ability of a user to be authorized to perform specific operations in the system. If the check result shows that the current user has permission to access, the key acquisition device will further process the request. At the same time, based on the access rights of the current user, the key acquisition device will adjust the second feature data and the preset loss threshold so that the feature loss result corresponding to the adjusted second feature data is less than or equal to the adjusted preset loss threshold, that is, the current user's access rights are also incorporated into the second feature data. The next time the user accesses the key, the adjusted second feature data can be referred to to increase the probability of obtaining the key, reduce the number of searches for the current user's access rights, and improve efficiency.

[0063] For example, if it detects that an account is logged in from a different location, the key acquisition device sends a text message to the staff, who then further confirms whether to allow the login. If the key acquisition device detects that the staff clicks the "Allow" button, the current access permission is set to allow access.

[0064] If the key acquisition device detects that the staff clicks the "Do Not Allow" button, the current access permission is set to not allow access, and the login information is recorded and saved in the exception log. The exception log can be used to adjust the access permission later.

[0065] Specifically, after the step of obtaining the target key data from the multiple segments of target password data, steps S43 to S45 are also included: Step S43, obtaining a historical key request instruction, and determining the usage frequency of the key based on the current key request instruction and the historical key request instruction; It should be noted that obtaining historical key request instructions means that the key acquisition device will collect and store records of past user key requests. These records are called "historical key request instructions" and contain detailed information about the user's request to access the key at different time points.

[0066] It should also be noted that the current key request instruction refers to the instruction currently issued by the user to request a key. The key acquisition device will compare this current request with the requests in the historical record.

[0067] By comparing the current request with the historical request, the key acquisition device can analyze how often a specific key is requested. The usage frequency refers to the number of times a key is requested within a certain period of time.

[0068] Understandably, this analysis is very important for security management, as it can help identify which keys are critical or frequently used, so that stricter security measures can be implemented for these keys, such as more frequent replacement, more complex encryption algorithms, or higher access control levels. It can also help identify possible abnormal behavior, such as a sudden increase in the frequency of requests for a certain key, which may be a sign of a security threat.

[0069] Step S44, determining a key update time based on the usage frequency and a preset key usage count; It should be noted that the usage frequency refers to the number of times a key is used within a certain period of time. This frequency can be the number of times a key is used per minute, per hour, per day, or any other time unit.

[0070] Additionally, the preset key usage count is a threshold pre-set in a security policy to define the maximum number of times a key can be used before it is considered "outdated" or "no longer secure".

[0071] In this embodiment, the specific steps include: First, the key acquisition device continuously monitors the usage of each key and records their usage frequency. Then, the key acquisition device compares the usage frequency of each key with the preset number of times of use.

[0072] Furthermore, if the usage frequency of the key approaches or reaches a preset number of times, the key acquisition device will calculate the time when the key should be updated, which may be immediately or at a certain point in the future, depending on the security policy.

[0073] It is understandable that once the key is used at a preset frequency, the key acquisition device may automatically generate a new key and replace the old key to ensure data security.

[0074] When the key needs to be updated, the key acquisition device will automatically update the key.

[0075] Step S45: Generate new target password data based on the key update time, and use the new target password data to replace the target password data.

[0076] The present application proposes a key acquisition method and related equipment. In the related technology, the key acquisition equipment generates a static key and directly reads it after obtaining a user request, which has low security. In the present application, first, a current key request is obtained, and in response to the current key request, first feature data corresponding to the current environment is obtained. Then, multiple segments of target password data corresponding to the key are loaded from the memory, and second feature data in the multiple segments of target password data are determined, wherein the target password data includes second feature data and target key data. Furthermore, based on the first feature data, the second feature data and a preset data feature loss model, a data feature loss result of the first feature data and the second feature data is obtained, wherein the preset data feature loss model is a trained data feature loss model. Finally, if the data feature loss result is less than or equal to a preset loss threshold, target key data is obtained from the multiple segments of target password data.

[0077] It can be understood that the key acquisition device obtains the environmental characteristics when the key request is made, and performs dynamic verification based on the environmental characteristics, thereby effectively improving the security of the key.

[0078] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can refer to the above introduction, and will not be repeated later. Figure 2 Before step S20, the key acquisition method further includes steps A201 to S203: Step A201, receiving a password generation instruction, and acquiring second characteristic data corresponding to the environmental information in response to the password generation instruction; It is understood that the key acquisition device receives an explicit instruction to generate a new password. This instruction may come from the user, another system, or an automated security policy.

[0079] After receiving the password generation instruction, the key acquisition device will perform corresponding operations in response to the instruction, which may include starting the password generation algorithm and preparing the resources and environment required to generate the password.

[0080] In the process of generating a password, the key acquisition device will collect characteristic data related to the current environment, which is called "second characteristic data". This data may include but is not limited to: the exact time when the password was generated, the geographical location information when the password was generated, the type of device that generated the password, the operating system, hardware configuration, etc., the user's behavior pattern before and after the password was generated, such as keyboard input speed, mouse movement pattern, network connection stability, speed, IP address, system load, memory usage, CPU usage, etc.

[0081] These environmental characteristics data will be used to enhance the complexity and security of the password. For example, the key acquisition device will use this data as a random number seed, or combine it with the password generation algorithm to ensure that the generated password has higher randomness and uniqueness.

[0082] Step A202, based on the second characteristic data, using a preset password generation algorithm to generate initial password data, wherein the initial password data includes target key data and second characteristic data; Step A203, segmenting the initial password data to obtain multiple segments of target password data, and randomly storing the target password data in different memories.

[0083] It is understandable that a complete cryptographic data (which may be a password, key, encrypted data, etc.) is segmented into multiple parts. The purpose of this is to increase the security of the data, because even if a part is leaked or stolen, the attacker cannot obtain the complete cryptographic data. After segmentation, the original cryptographic data is converted into multiple smaller data segments, each of which contains a part of the original data. These data segments are called "target cryptographic data".

[0084] These segments are randomly stored in different memory locations on the computer. This random storage is intended to further increase security, because even if an attacker is able to access part of the memory, it will be difficult for them to predict and find the exact location of all the stored password data.

[0085] It should be noted that different memories refer to different areas of physical memory, or different parts of virtual memory, or even different storage devices (such as hard disks, SSDs, memory sticks, etc.).

[0086] By segmenting and storing password data randomly, data security can be improved. This method can prevent a single attack point from causing the leakage of the entire password data and increase the difficulty for attackers to obtain complete data.

[0087] In this embodiment, by combining environmental feature data, the password generation process can become more secure because even if the password generation algorithm is cracked, it is difficult for an attacker to copy or predict the generated password without the corresponding environmental feature data.

[0088] Based on the first and second embodiments of the present application, in the third embodiment of the present application, the same or similar contents as those of the first and second embodiments can be referred to the above description, and will not be described in detail later. Figure 3 Before step S30, the key acquisition method further includes steps A301 to S305: Step A301, obtaining a current data feature loss model, first sample data, and second sample data, wherein the data feature loss results of the first sample data and the second sample data are the first data feature loss results; Step A302, obtaining second data feature loss results of the first sample data and the second sample data based on the current data feature loss model, the first sample data, and the second sample data; Step A303, calculating the first data feature loss result and the second data feature loss result to obtain a loss difference; Step A304: if the loss difference is greater than a preset loss difference, adjusting the parameters of the current data feature loss model and recording the number of adjustments; It is to be understood that the loss difference is compared with a preset loss difference to determine whether they are the same or similar.

[0089] It is understandable that the purpose of adjusting parameters is to improve the accuracy, consistency and generalization ability of the model, ensuring that the model can produce stable and reliable output when faced with the same input. By adjusting parameters, the performance of the model can be optimized to better suit a specific task or data set.

[0090] This process is usually iterative, requiring multiple comparisons of inference results and adjustments of parameters until the model's performance reaches a satisfactory level.

[0091] Step A305, based on the adjusted current data feature loss model, returns to the step of obtaining the second data feature loss result of the first sample data and the second sample data based on the current data feature loss model, the first sample data and the second sample data, until the loss difference is less than or equal to the preset loss difference, or the number of adjustments is equal to the preset number of adjustments, and sets the current data feature loss model corresponding to the minimum loss difference as the preset data feature loss model.

[0092] The sample data is processed using the adjusted model to generate the second data feature loss result. This step is repeated until the output of the model meets specific conditions.

[0093] This process continues until the loss difference is less than or equal to the preset loss difference, which means that the model has achieved consistency during the processing and produces the same output for the same input.

[0094] It is understandable that once the loss difference is less than or equal to or greater than the preset loss difference, it indicates that the model has been adjusted to an ideal state, and the model in this state is called the "preset data feature loss model". This "preset data feature loss model" is optimized and can stably process sample data and produce consistent results.

[0095] In this embodiment, continuous adjustment and testing are performed to ensure that the data feature loss model can produce consistent and reliable second data feature loss results when processing sample data. This process is crucial to improving the stability and reliability of the model, especially in application scenarios that require high consistency in model output.

[0096] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the key acquisition method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0097] This application also provides a key acquisition device, please refer to Figure 4 , the key acquisition device comprises: An acquisition instruction module 10, the acquisition instruction module is used to acquire a current key request, and in response to the current key request, acquire first characteristic data corresponding to the current environment; A determination module 20, the determination module is used to load multiple segments of target cryptographic data corresponding to the key from a memory, and determine second characteristic data in the multiple segments of target cryptographic data, wherein the target cryptographic data includes the second characteristic data and target key data; A calculation module 30, the calculation module is used to obtain data feature loss results of the first feature data and the second feature data based on the first feature data, the second feature data and a preset data feature loss model, wherein the preset data feature loss model is a trained data feature loss model; The key acquisition module 40 is used to acquire target key data from the multiple segments of target password data if the data feature loss result is less than or equal to a preset loss threshold.

[0098] In one embodiment, the determining module includes: A receiving unit, configured to receive a password generation instruction, and acquire second characteristic data corresponding to the environmental information in response to the password generation instruction; A generating unit, configured to generate initial password data based on the second characteristic data using a preset password generation algorithm, wherein the initial password data includes target key data and the second characteristic data; The segmentation unit is used to segment the initial password data to obtain multiple segments of target password data, and randomly store the target password data in different memories.

[0099] In one embodiment, the determining module further includes: The loading unit loads multiple groups of target cryptographic data corresponding to the key from the memory; A first acquisition unit, used to obtain the correlation between two sets of target password data based on a preset data matching relationship algorithm; The splicing unit is used to splice the two groups of target password data with the greatest correlation to obtain initial password data and determine the characteristic information in the initial password data.

[0100] In one embodiment, the key acquisition module includes: A second acquisition unit, configured to acquire target key data from the target cryptographic data if the data feature loss result is less than or equal to a preset loss threshold; The third acquisition unit is used to obtain the current access permission if the data feature loss result is greater than a preset loss threshold, and to obtain the key data from the target password data if the current access permission is to allow access.

[0101] In one embodiment, the key acquisition module further includes: A first determining unit, configured to obtain a historical key request instruction, and determine a usage frequency of a key based on the current key request instruction and the historical key request instruction; A second determining unit, configured to determine a key update time based on the usage frequency and a preset key usage count; The replacement unit is used to generate new target cryptographic data based on the key update time, and replace the target cryptographic data with the new target cryptographic data.

[0102] In one embodiment, the calculation module includes: a fourth acquisition unit, configured to acquire a current data feature loss model, first sample data, and second sample data, wherein data feature loss results of the first sample data and the second sample data are first data feature loss results; a fifth acquisition unit, configured to obtain a second data feature loss result of the first sample data and the second sample data based on the current data feature loss model, the first sample data, and the second sample data; A calculation unit, configured to calculate the first data feature loss result and the second data feature loss result to obtain a loss difference; A judgment unit, configured to adjust the parameters of the current data feature loss model if the loss difference is greater than a preset loss difference, and record the number of adjustments; A training unit is used to return the step of obtaining the second data feature loss result of the first sample data and the second sample data based on the current data feature loss model, the first sample data and the second sample data, based on the adjusted current data feature loss model, until the loss difference is less than or equal to the preset loss difference, or the number of adjustments is equal to the preset number of adjustments, and set the current data feature loss model corresponding to the minimum loss difference as the preset data feature loss model.

[0103] The key acquisition device provided by the present application adopts the key acquisition method in the above embodiment, which can solve the technical problem of key acquisition. Compared with the prior art, the beneficial effects of the key acquisition device provided by the present application are the same as the beneficial effects of the key acquisition method provided by the above embodiment, and other technical features in the key acquisition device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0104] The present application provides a key acquisition device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the key acquisition method in the above-mentioned embodiment one.

[0105] Reference below Figure 5 , which shows a schematic diagram of the structure of a key acquisition device suitable for implementing the embodiment of the present application. The key acquisition device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The key acquisition device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0106] like Figure 5 As shown, the key acquisition device may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the key acquisition device are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the key acquisition device to communicate with other devices wirelessly or by wire to exchange data. Although the key acquisition device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0107] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0108] The key acquisition device provided by the present application adopts the key acquisition method in the above embodiment to solve the technical problem of key acquisition. Compared with the prior art, the beneficial effects of the key acquisition device provided by the present application are the same as the beneficial effects of the key acquisition method provided by the above embodiment, and other technical features in the key acquisition device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0109] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0110] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0111] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the key acquisition method in the above-mentioned embodiment.

[0112] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0113] The computer-readable storage medium may be included in the key acquisition device; or may exist independently without being assembled into the key acquisition device.

[0114] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the key acquisition device, the key acquisition device: Obtaining a current key request, and in response to the current key request, obtaining first characteristic data corresponding to the current environment; Loading multiple segments of target cryptographic data corresponding to the key from the memory, and determining second characteristic data in the multiple segments of target cryptographic data, wherein the target cryptographic data includes the second characteristic data and target key data; Based on the first feature data, the second feature data and a preset data feature loss model, obtaining data feature loss results of the first feature data and the second feature data, wherein the preset data feature loss model is a trained data feature loss model; If the data feature loss result is less than or equal to a preset loss threshold, target key data is obtained from the multiple segments of target password data.

[0115] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0116] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0117] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0118] The readable storage medium provided in the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned key acquisition method, and can solve the technical problem of key acquisition. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the present application are the same as the beneficial effects of the key acquisition method provided in the above-mentioned embodiment, and will not be repeated here.

[0119] The present application also provides a computer program product, including a computer program, which implements the steps of the key acquisition method as described above when executed by a processor.

[0120] The computer program product provided by the present application can solve the technical problem of key acquisition. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the key acquisition method provided by the above embodiment, which will not be repeated here.

[0121] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A key acquisition method, characterized in that: The key acquisition method comprises: Obtaining a current key request, and in response to the current key request, obtaining first characteristic data corresponding to the current environment; Loading multiple segments of target cryptographic data corresponding to the key from the memory, and determining second characteristic data in the multiple segments of target cryptographic data, wherein the target cryptographic data includes the second characteristic data and target key data; Based on the first feature data, the second feature data and a preset data feature loss model, obtaining data feature loss results of the first feature data and the second feature data, wherein the preset data feature loss model is a trained data feature loss model; If the data feature loss result is less than or equal to a preset loss threshold, target key data is obtained from the multiple segments of target password data.

2. The key acquisition method according to claim 1, characterized in that: Before the step of loading the multiple segments of target password data corresponding to the key from the memory, the method further includes: receiving a password generation instruction, and acquiring second characteristic data corresponding to the environmental information in response to the password generation instruction; Based on the second characteristic data, using a preset password generation algorithm to generate initial password data, wherein the initial password data includes target key data and the second characteristic data; The initial password data is segmented to obtain multiple segments of target password data, and the target password data is randomly stored in different memories.

3. The key acquisition method according to claim 1, characterized in that: The step of loading multiple sections of target cryptographic data corresponding to the key from the memory and determining the second characteristic data in the multiple sections of target cryptographic data further includes: Loading multiple sets of target cryptographic data corresponding to the key from the memory; Based on a preset data matching relationship algorithm, the correlation between two sets of target password data is obtained; The two groups of target password data with the greatest correlation are spliced ​​to obtain initial password data, and characteristic information in the initial password data is determined.

4. The key acquisition method according to claim 1, characterized in that: If the data feature loss result is less than or equal to a preset loss threshold, the step of obtaining target key data from the multiple segments of target password data also includes: If the data characteristic loss result is less than or equal to a preset loss threshold, obtaining target key data from the target password data; If the data feature loss result is greater than a preset loss threshold, the current access permission is obtained; if the current access permission is to allow access, the key data is obtained from the target password data.

5. The key acquisition method according to claim 1, characterized in that: After the step of obtaining the target key data from the multiple segments of target password data, the method further includes: Obtaining a historical key request instruction, and determining a usage frequency of a key based on the current key request instruction and the historical key request instruction; Determining a key update time based on the usage frequency and a preset number of key usage times; Based on the key update time, new target cryptographic data is generated, and the target cryptographic data is replaced with the new target cryptographic data.

6. The key acquisition method according to claim 1, characterized in that: Before the step of based on the environmental information data, the characteristic information data and the preset data characteristic loss model, it also includes: Obtaining a current data feature loss model, first sample data, and second sample data, wherein the data feature loss results of the first sample data and the second sample data are the first data feature loss results; Based on the current data feature loss model, the first sample data, and the second sample data, obtaining second data feature loss results of the first sample data and the second sample data; Calculating the first data feature loss result and the second data feature loss result to obtain a loss difference; If the loss difference is greater than a preset loss difference, the parameters of the current data feature loss model are adjusted, and the number of adjustments is recorded; Based on the adjusted current data feature loss model, return to the step of obtaining the second data feature loss result of the first sample data and the second sample data based on the current data feature loss model, the first sample data and the second sample data, until the loss difference is less than or equal to the preset loss difference, or the number of adjustments is equal to the preset number of adjustments, and set the current data feature loss model corresponding to the minimum loss difference as the preset data feature loss model.

7. A key acquisition device, characterized in that: The key acquisition device comprises: An acquisition instruction module, the acquisition instruction module is used to acquire a current key request, and in response to the current key request, acquire first characteristic data corresponding to the current environment; A determination module, the determination module is used to load multiple segments of target cryptographic data corresponding to the key from a memory, and determine second characteristic data in the multiple segments of target cryptographic data, wherein the target cryptographic data includes the second characteristic data and target key data; A calculation module, wherein the calculation module is used to obtain data feature loss results of the first feature data and the second feature data based on the first feature data, the second feature data and a preset data feature loss model, wherein the preset data feature loss model is a trained data feature loss model; A key acquisition module is used to acquire target key data from the multiple segments of target password data if the data feature loss result is less than or equal to a preset loss threshold.

8. A key acquisition device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the key acquisition method according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the key acquisition method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the key acquisition method according to any one of claims 1 to 6 are implemented.

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